芮一康 - 东南大学

个人简介

芮一康，博士，副研究员，博导，现任：东南大学交通学院智慧交通系副系主任，中国公路学会自动驾驶工作委员会副秘书长，车路协同创新联合体副秘书长，WTC车路云协同与智慧公路应用技术委员会主席，国际路联（IRF）CulturalRoad IPG member，中国人工智能学会智能交通专业委员会委员，入选江苏省“双创”计划，获中国公路学会2016-2021年优秀个人会员，并担任多个国内外知名期刊和会议审稿人。围绕智能网联交通/车路协同自动驾驶，开展产学研用，在SCI/SSCI检索期刊上发表学术论文20余篇，牵头或参与标准编制8项，获得中国公路学会科技进步奖特等奖、中国生产力促进中心协会一等奖等荣誉。教育背景多学科交叉融合背景： 2005 年本科毕业于南京农业大学计算机科学与技术专业， 2008 年硕士毕业于南京大学地理信息系统专业， 2013 年博士毕业于瑞典皇家工学院 (KTH) 空间信息科学专业，随后在南京大学进行博士后研究工作。工作经历 2017 年 3 月进入东南大学交通学院交通工程系任副研究员以来，一直从事智能网联交通 / 车路协同自动驾驶相关研究。

研究领域

1 ）智能网联交通 / 车路协同：智能网联环境下智能驾驶高精地图构建、基于 AI 的车路协同感知、规划决策和控制研究。 2 ）交通感知与场景理解：跨场景感知泛化、感知大小模型协调优化、复杂交通场景理解研究。 3 ）自动驾驶 / 群体智能的路径规划：车辆轨迹预测、基于深度强化学习的分布式多智能体协同优化研究。

近期论文

查看导师新发文章（温馨提示：请注意重名现象，建议点开原文通过作者单位确认）

[1] Wu, R., Jiang, J., Lu, W., Rui, Y.*, et al. (2025) A Dual-Layer Path Planning Approach for Ramp Merging with Integrated Risk Management. Expert Systems with Applications, 2025.3: 115383. [2] Zhao, Y., Wang, C., Rui, Y.*, et al. (2025) Bidirectional Temporal Convolutional Graph Attention Networks for Key Node Identification in Traffic Monitoring. IEEE Transactions on Intelligent Transportation Systems, 26(6), 8720. [3] Wu, R., Li, L., Shi, H., Rui, Y.* , Ngoduy, D., Ran, B. (2024). Integrated driving risk surrogate model and car-following behavior for freeway risk assessment . ACCIDENT ANALYSIS AND PREVENTION, 201, 107571. [4] Rui, Y., Zhao, Y., Lu, W., Wang, C. (2024). Dynamic Tensor Modeling for Missing Data Completion in Electronic Toll Collection Gantry Systems. SENSORS, 24(1). [5] Lu, W., Yi, Z., Gu, Y., Rui, Y.* , Ran, B. (2023). TD3LVSL: A lane-level variable speed limit approach based on twin delayed deep deterministic policy gradient in a connected automated vehicle environment. Transportation Research Part C: Emerging Technologies, 153, 104221. [6] Zhao, Y., Lu, W., Rui, Y.* , Ran, B. (2023). Classification of the Traffic Status Subcategory with ETC Gantry Data: An Improved Support Tensor Machine Approach. Journal of Advanced Transportation, 2765937. [7] Lu, W; Rui, Y.* ; Ran, B. (2022). Lane-level traffic speed forecasting: a novel mixed deep learning model. IEEE Transactions on Intelligent Transportation Systems, 23(4): 3601-3612. [8] Lu, W., Yi, Z., Liu, W., Gu, Y., Rui, Y.* and Ran, B. (2020). Efficient deep learning based method for multi-lane speed forecasting: a case study in beijing. IET Intelligent Transport Systems. 14(14), 2073-2082. [9] Lu, W., Rui, Y.* , Yi, Z., Ran, B., and Gu, Y. (2020). A hybrid model for lane-level traffic flow forecasting based on complete ensemble empirical mode decomposition and extreme gradient boosting. IEEE Access, 8: 42042. [10] Rui, Y. , Yang, Z., Qian, T., Khalid, S., Xia, N. and Wang, J. *, (2016). Network-constrained and category-based point pattern analysis for Suguo retail stores in Nanjing, China. International Journal of Geographical Information Science (IJGIS). DOI: 10.1080/ 13658816.2015.1080829. [11] Rui, Y. , Huang, H., Lu, M., Wang, B., and Wang, J.*, (2016) A Comparative Analysis of the distributions of KFC and McDonald’s Outlets in China. ISPRS International Journal of Geo-Information. 5(3), 27-37. [12] Rui, Y. , Shen, D., Khalida, S., Yang, Z., and Wang, J.*, (2015). GIS-based emergency response system for sudden water pollution accidents. Physics and Chemistry of the Earth. 79-82, 115-121. [13] Rui, Y.* and Ban, Y., (2014). Exploring the relationship between street centrality and land use in Stockholm. International Journal of Geographical Information Science (IJGIS), 28:7, 1425-1438. [14] Rui, Y.* , Wu, W., Shen, D. and Wang, J., (2014). Influence of the nearest-neighbor connections on shaping weighted evolving network. Chaos, Solitons and Fractals, 69, 172-178.

学术兼职

中国公路学会自动驾驶工作委员会副秘书长，车路协同创新联合体副秘书长， WTC“ 车路云协同与智慧公路应用”技术委员会主席，国际路联（ IRF ） CulturalRoad IPG member，中国人工智能学会智能交通专业委员会委员。